Modeling and optimization of machining parameters to minimize surface roughness and maximize productivity when turning polytetrafluoroethylene (PTFE)

The objective of this work is to study the impact of the machining parameters ( ap , f , and Vc ) on the technological parameters, surface roughness criteria (Ra, Rz), and material removal rate (MRR) during the turning of polytetrafluoroethylene (PTFE) polymer. The machining tests were carried out using a square metal carbide insert in compliance with the Taguchi design (L27). ANOVA was used to determine the influence and contribution of machining parameters ( ap , f , and Vc ) on the output parameters ( Ra , Rz , and MRR ). It was indicated that the surface roughness and the material removal rate are strongly affected by the feed rate with contributions of 90.02, 91.81, and 49.22% for Ra , Rz , and MRR , respectively. The response surface methodology (RSM) and the artificial neural networks (ANN) approach were used for output technological parameter modeling to discern the most efficient one. Finally, the desirability function (DF) was used to determine optimal cutting parameters. The optimization was carried out using three approaches, which are quality, productivity, and the combination of quality and productivity. The results showed that the optimal parameters for minimizing roughness and maximizing MRR were found as ap = 2 mm, f = 0.126 mm/rev, and Vc = 270 m/min.